Network models of financial stability by Dr. Davide Cellai and an introduction to statistical network analysis by Dr. Rastelli, UCD.
Please note this is counted as 0.5 of a training day per employee registered for all Enterprise Alliance members.
2pm: Dr. Davide Cellai, Central Bank of Ireland presents Network models of financial stability
Brief synopsis of lecture content: The financial sector is regulated by authorities whose main objective is safeguarding financial stability. An important source of risk in the financial sector is related to the interconnectedness of institutions due a number of reasons (e.g. asset correlation or common exposures). A natural way of modelling interconnectedness in the financial sector is using approaches from network science.
This talk will briefly review the literature on the subject and focus on a specific problem: credit concentration risk arising when banks lend money to the same counterparties. Dr. Cellai will present a simple network model that quantifies the systemic risk associated with this particular aspect from a regulatory perspective
3-5pm Dr. Riccardo Rastelli, UCD, An introduction to statistical network analysis
Brief synopsis of lecture content:
Nowadays, large amounts of stored data describe how entities interact with each other. For example, these data may represent friendship relations between scholars, coauthorship relations between researchers, mutual claims between financial institutions, or functional connectivity between different areas of the brain. Random graphs are the mathematical tools that are used to represent these interaction datasets.
Researchers and practitioners are often interested in modelling the random graphs, and in understanding their structures and capturing some of their features of interest. For these purposes, a number of statistical models have been introduced in recent times. One family of these statistical models relies on a “latent variable” structure, whereby one assumes that the nodes are characterised by some latent information that determines their connectivity behaviour.
This session, will focus on two latent variable models for random graphs: the stochastic block model and the latent position model. I will introduce the theory behind these models, and give an overview of their mathematical properties. Then, I will focus on the R packages that can be used to fit them, and I will coordinate an interactive session where the models will be used to analyse real datasets.
Please ensure you have a laptop with R installed https://www.r-project.org/Additional R packages that will be used: igraph, statnet, latentnet, blockmodels, dynsbm
Speaker biography: Davide Cellai is a scientist that works as senior data scientist at the Central Bank of Ireland since 2017. He has a MSc in Physics from the State University of Milan, Italy, and a PhD in Physical Chemistry from the University College Dublin (UCD), Ireland. He has been working in academic research in the School of Computer Science in UCD (2008-2010) and in the Department of Mathematics and Statistics at the University of Limerick (2011-2015). Since 2015 he has been working in the area of Data Science, developing mathematical and statistical models in topics including financial networks, consumer behaviour, anomaly detection, natural language processing. He is an author of 19 peer-reviewed scientific papers on international journals, with more than 600 citations, and he has presented his works in leading international conferences in complex systems, computer science and applied mathematics.
Dr. Riccardo Rastelli is Lecturer at the School of Mathematics and Statistics, University College Dublin. His research focuses on statistical methodologies for the analysis of complex networks
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